AI / GenAI Solutions Engineer

SOUM; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Soum is seeking a Senior GenAI Engineer to design and ship production-grade AI systems touching millions of users across the buying and selling journey. You will architect LLM-powered services on a Python backend, integrate them into product surfaces on a React frontend, and collaborate across teams to ship high-impact AI features.

You’ll own end-to-end development from problem framing and model selection to deployment, monitoring, and iteration, with emphasis on reliability, cost efficiency,

Qualifications

• 5+ years building production software.
• 2+ years shipping LLM/ML features at scale.
• Strong Python for backend services and ML tooling.
• Experience with TypeScript and React for frontend integration.
• Production experience with major LLM providers (Gemini, Claude, GPT).
• Deep understanding of Retrieval Augmented Generation (RAG).
• Experience with embeddings and vector search (HNSW, IVF, etc.).
• Familiarity with relational DBs (PostgreSQL) and caching (Redis).
• Comfort with observability, A/B testing, and safe rollouts.

Responsibilities

• Architect production GenAI systems across domains such as chat, orders, discovery, and content generation.
• Own features end-to-end from framing to deployment and monitoring.
• Design agentic workflows with tool calls and multi-step reasoning.
• Build the retrieval and embeddings stack including vector indexes and hybrid search.
• Improve reliability and cost efficiency with caching and latency budgets.
• Establish evaluation rigor with offline/online evals and KPIs.
• Drive experimentation by evaluating new models and patterns for production.
• Mentor engineers on AI/ML best practices and production readiness.
• Partner cross-functionally to identify AI opportunities and ship them.

Skills

Production software

Python backend

TypeScript/React

LLM tooling

RAG (Retrieval Augmented Generation)

Vector databases

Embeddings

ML fundamentals

Scripting & automation

Observability & A/B testing

Tools

pgvector

Pinecone

Weaviate

Redis

PostgreSQL

FastAPI

Job description

Role Name: AI / GenAI Solutions Engineer

Location: Egypt, Pakistan (Remote)

Work Week: Sunday – Thursday

Working Hours: 9:00 AM – 6:00 PM (Saudi Arabia Standard Time)

Overview:

Soum is building an AI native layer across our C2C marketplace, from customer conversations to automated order handling, personalised discovery, recommendations, fraud signals, and seller tooling. We’re looking for a Senior GenAI Engineer to design and ship production-grade AI systems that touch millions of users across the buying and selling journey.

You’ll work end-to-end: architecting LLM-powered services on our Python backend, integrating them into product surfaces on our React frontend, and partnering with teams across the company to find where AI genuinely moves the needle. This is a senior builder’s role with high autonomy, broad scope, and real impact on the business.

What You’ll Do

• Architect production GenAI systems across multiple domains, including conversational agents, automated order and dispute workflows, personalized discovery and recommendations, content generation, search relevance, and emerging use cases.

• Own features end-to-end , from problem framing and model selection through backend services (FastAPI, Python), frontend integration (React, TypeScript), evaluation, deployment, and monitoring.

• Design agentic workflows with tool calling, multi-step reasoning, retrieval augmented generation, and integrations with internal APIs, third-party SaaS, and event-driven systems.

• Build the retrieval and embeddings stack , including chunking strategies, embedding model selection, vector indexes, hybrid search, reranking, and retrieval evaluation pipelines.

• Make it reliable and cost-efficient through streaming, prompt caching, latency budgets, token cost optimization, observability for LLM calls, and graceful fallback when models or upstreams misbehave.

• Establish evaluation rigor with offline and online evals covering response quality, tool call correctness, hallucination rate, retrieval precision, and business KPIs.

• Drive experimentation and research by evaluating new models, frameworks, and agent patterns, running focused experiments, and bringing what works into production.

• Mentor and raise the bar for engineers across the team on AI and ML best practices, prompt engineering, and production readiness.

• Partner cross-functionally with Product, Engineering, Data, Ops, and CX to identify high-leverage AI opportunities and ship them.

Where You’ll Have Impact

We’re actively building in or want to build the following non-exhaustive list of areas:

Conversational AI for customer support, dispute resolution, and seller assistance

Automated order handling, escalation routing, and workflow orchestration

Personalized discovery, recommendations, and search relevance

Listing quality, including auto-generated titles, descriptions, categorization, and image understanding

Trust and safety, including fraud signals, anomaly detection, and content moderation

Internal agent tooling for ops and CX teams

Qualifications
Required

• 5+ years building production software , with at least 2 years shipping LLM and ML-powered features at scale.
• Strong Python for backend services, scripting, data pipelines, and ML tooling.
• Working ability in TypeScript and React for integrating AI features directly into product surfaces.
• Production experience with major LLM providers (Gemini, Claude, GPT) covering tool and function calling, structured outputs, streaming, prompt caching, and cost control.
• Deep understanding of Retrieval Augmented Generation (RAG): document ingestion, chunking, embedding generation, vector databases (pgvector, Pinecone, Weaviate, or similar), hybrid retrieval, and reranking.
• Solid grounding in embeddings and vector search : dense vs. sparse representations, similarity metrics, indexing strategies (HNSW, IVF), and dimensionality tradeoffs.
• Strong ML and NLP fundamentals : transformer architectures, tokenization, fine-tuning vs. prompting tradeoffs, classification, ranking, and evaluation methodology.
• Experience with scripting and automation for data preparation, model evaluation harnesses, and offline analysis.
• Comfortable with relational databases (PostgreSQL), caching layers (Redis), REST, SSE, WebSockets, and event-driven architectures.
• Production experience with observability, A/B testing, and rolling out model changes safely.
  Nice to Have
• Experience with recommendation systems, learning to rank, or search relevance at scale.
• Marketplace or C2C background covering buyer and seller dynamics, disputes, fraud, and payouts.
• Multimodal model experience, including vision and image understanding for listings.
• Arabic NLP or bilingual product experience.
• Experience with agent frameworks (LangGraph, custom orchestrators) and the judgment to know when to use them.
• Fine-tuning, LoRA, distillation, or hosting open weight models in production.
• Open source contributions to LLM tooling, eval frameworks, or retrieval libraries.

What We Care About

• Ship over the architect. Lean code, no premature abstractions, no half-finished frameworks.

• Measurement-driven development. Features ship with evals and metrics, not vibes.

• Ownership. From idea to deployment to monitoring the first real users.

• Curiosity and range. This role spans many problem domains, and we want someone energized by that.